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.fuse() gradient introduction bug fix
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@ -104,8 +104,8 @@ def prune(model, amount=0.3):
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def fuse_conv_and_bn(conv, bn):
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# https://tehnokv.com/posts/fusing-batchnorm-and-conv/
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with torch.no_grad():
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# Fuse convolution and batchnorm layers https://tehnokv.com/posts/fusing-batchnorm-and-conv/
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# init
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fusedconv = nn.Conv2d(conv.in_channels,
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conv.out_channels,
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@ -113,7 +113,7 @@ def fuse_conv_and_bn(conv, bn):
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stride=conv.stride,
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padding=conv.padding,
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groups=conv.groups,
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bias=True).to(conv.weight.device)
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bias=True).requires_grad_(False).to(conv.weight.device)
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# prepare filters
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w_conv = conv.weight.clone().view(conv.out_channels, -1)
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